SETD2 variation correlates with tumor mutational burden and MSI along with improved response to immunotherapy

Abstract

Background: SETD2 protects against genomic instability via maintenance of homologous recombination repair (HRR) and mismatch repair (MMR) in neoplastic cells. However, it remains unclear whether SETD2 dysfunction is a complementary or independent factor to microsatellite instability-high (MSI-H) and tumor mutational burden-high (TMB-H) for immunocheckpoint inhibitor (ICI) treatment, and little is known regarding whether this type of dysfunction acts differently in various types of cancer.

Methods: This cohort study used multidimensional genomic data of 6726 sequencing samples from our cooperative and non-public GenePlus institute from April 1 through April 10, 2020. MSIsensor score, HRD score, RNAseq, mutational data, and corresponding clinical data were obtained from the TCGA and MSKCC cohort for seven solid tumor types.

Results: A total of 1021 genes underwent target panel sequencing reveal that SETD2 mutations were associated with a higher TMB. SETD2 deleterious mutation dysfunction affected ICI treatment prognosis independently of TMB-H (p < 0.01) and had a lower death hazard than TMB-H in pancancer patients (0.511 vs 0.757). Significantly higher MSI and lower homologous recombination deficiency were observed in the SETD2 deleterious mutation group. Improved survival rate was found in the MSKCC-IO cohort (P < 0.0001) and was further confirmed in our Chinese cohort.

Conclusion: We found that SETD2 dysfunction affects ICI treatment prognosis independently of TMB-H and has a lower death hazard than TMB-H in pancancer patients. Therefore, SETD2 has the potential to serve as a candidate biomarker for ICI treatment. Additionally, SETD2 should be considered when dMMR is detected by immunohistochemistry.

Keywords: Immune checkpoint inhibitors; Microsatellite instability; SETD2 mutation; Tumor microenvironment; Tumor mutation burden.

Fig.1

A Incidence of SETD2 deleterious mutations in pan-cancer. Red, green, and blue bars represent the frequency of SETD2 nonsynonymous mutations in pan-cancer in the Geneplus cohort. (Nonsynonymous mutations include frameshift indels, inframe indels, missense mutations, nonsense mutations, nonstop mutations, and translation start site mutations.) B The domains and the corresponding mutation sites of SETD2 mutations. Domains and the corresponding mutation sites of the SETD2 gene identified in the Geneplus cohort. Green, red, blue, brown, orange, and purple dots represent Missense_Mutation, Nonsense_Mutation, Frame_Shift_Del, In_Frame_Del, Splice_Site, and Frame_Shift_Ins, respectively. C Proportion of SETD2 mutation forms by cohort and cancer type

Fig. 2

A Correlation between SETD2 deleterious mutations and TMB. The difference of TMB in patients with SETD2 deleterious mutations and non-deleterious mutations across different cancer types in the GenePlus cohort. B Difference of tumor mutation burden (TMB) in patients with diverse molecular features (SETD2 deleterious mutations, BRCA1/2 deleterious mutations, MMR genes deleterious mutations, or POLE/D1 deleterious mutations) from the GenePlus cohort (Wilcoxon rank-sum test; ****, P < 0.0001; ***, P < 0.001; **, P < 0.01; *, P < 0.05.)

Fig. 3

Correlation between SETD2 deleterious mutations, MSI, and HRD. A Differences in MSIsensor scores in patients with SETD2 deleterious mutations and non-deleterious mutations in the TCGA cohort across seven cancer types. B Odds ratios and 95% confidence intervals calculated by multivariate binary logistic regression comparing the risk of MSI-H (MSIsensor score ≥ 4) for patients with and without mutated genes in endometrial carcinoma, colorectal carcinoma, and stomach adenocarcinoma. C Differences in HRD scores in patients with SETD2 deleterious mutations and non-deleterious mutations in the TCGA cohort across seven cancer types

Fig. 4

Tumors with SETD2 deleterious mutations exhibit an inflamed immune microenvironment. A Different fractions of seven types of immune cells estimated by the CIBERSORT deconvolution algorithm between SETD2 deleterious mutation and SETD2 non-deleterious mutation groups. Samples were taken from patients across seven types of cancer in the TCGA cohort (bladder urinary cancer, colorectal adenocarcinoma, renal carcinoma, NSCLC, skin cutaneous melanoma, stomach adenocarcinoma, and endometrial carcinoma) (N = 2360). B Comparison of the expression of immune-related gene profiles between the SETD2 non-deleterious mutation group and the deleterious mutation group. Samples were taken from patients across seven cancer types in the TCGA cohort (bladder urinary cancer, colorectal adenocarcinoma, renal carcinoma, NSCLC, skin cutaneous melanoma, stomach adenocarcinoma, and endometrial carcinoma)

Fig. 5

A Overall survival (OS) and progression free survival (PFS) curves of immune checkpoint inhibitor (ICI)-treated patients. B ORR rates and DCR rates of patients with PD-1/PD-L1 inhibitor monotherapy, or combined therapy with other drugs. C Mutation sites and types of SETD2 mutation in ICI-treated patients. D Response evaluation criteria in solid tumors (PR, partial response; SD, stable disease; PD, progression disease), cancer types, SETD2 mutation status, and treatment types of GenePlus ICI-treated patients. E SETD2 deleterious mutations are linked with improved survival outcome in the ICI-treatment cohort